5 Ways Small and Midsized Manufacturing Is Using IoT Data

The Internet of Things (IoT) is by all definitions a big concept. Different people have different opinions about the specifics, but the big picture of sending lots of data about lots of different factors from a wide array of devices and sources is consistent.

Most companies look to the IoT to tell them what internal operations look like. Food storage coolers are more easily monitored for environmental conditions. Delivery trucks and equipment are trackable both for location and for how they are performing. Retailers can even create cashier-less stores using the radio-frequency identification tags on items and customers’ phones.

Manufacturers can employ IoT to do more than just track things inside factory walls or on delivery trucks. Everything that is sold and distributed was made by a manufacturer. Everything in the IoT was made by a manufacturer. When those items get to customers, the manufacturer receives data from their own devices. Combine these data with data from production machines inside the factory, and manufacturers have considerable data to work with.

This setup isn’t limited to large manufacturers. Small and midsized manufacturers are also using IoT data to help themselves and their customers, as the following five examples show. These implementations are not much different than what big manufacturers can do—except small and midsized companies can use a more focused array of products that let them use IoT data in ways that separate them from their larger competitors.

Customer Service

This IoT data application almost seems self-evident. If a manufacturer sees the sensor data coming from its products, the manufacturer should have a good idea of when and why products are not functioning properly. When in conversation with an irate customer, the manufacturer is much better armed with information using the data coming from its IoT data streams. Certainly, the incoming data have to be interpreted using analytic models to create information understandable to humans. Once that is done, the customer representative knows a heck of a lot about the usage history of all items at the customer’s location.

Predictive Ordering

Customers’ consumable items need to be replenished. Those manufactured items have to be reordered, and it is incumbent upon the salesperson to make sure the customer doesn’t start ordering product from a competitor. Timely or effortless reordering is extremely effective in customer retention.

Still, a balance is needed: salespeople cannot be pushy about reorders, but the customer doesn’t want to run the risk of running out of consumables. In the middle, people have relied on an order schedule or the customer’s ERP system to prompt an order. With IoT data streams, the manufacturer examines the state and quantity of its items at customer locations. These data let the manufacturer tell the customer when they need to reorder and even puts needed items on the manufacturer’s production schedule.

Maintenance Contracts

Many manufacturers make a good deal of their money from support or after-sales contracts for services. IoT data allow the manufacturer’s systems to determine how items are performing at the customer site and dispatch service personnel when needed or even before they are needed. The IoT data turn what might be a problem in the future into a chance to shine as a vendor.

Quality Control

Traditional manufacturing examined work in progress and finished goods inside the factory walls. The IoT lets manufacturers see how their products hold up over time and use. Manufacturers can more quickly spot persistent or consistent problems across multiple customers rather than waiting for the customer service database to get enough records to show a pattern. Knowing persistent failures in the field directs efforts to better design or manufacturing procedures.

Supply Chain

Visibility into the supply chain helps small and midsized manufacturers plan production and inventory processes better. Production planners see interpreted IoT data streams showing exactly where items are in shipment from vendors. Before IoT adoption, access to this supply chain information required systems integration or a lot of manual communications. Today, sharing IoT stream data is easy, or at least easier, to maintain once setup is complete and the means to interpret location data has been created.

About the Author

David Gillman has worked in software and technology-related services for more than 20 years. He has been a user and administrator of CRM systems as well as a pioneer in analytical CRM. David currently works on hands-on analytical CRM projects in several industries, publishes on the subject, and is a speaker at industry conferences. David is an analyst with Studio B.